Examinando por Autor "Norambuena, Margarita"
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Ítem A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control(Institute of Electrical and Electronics Engineers Inc., 2018) Norambuena, Margarita; Rodriguez, José; Zhang, Zhenbin; Wang, Fengxiang; García, Cristian; Kennel, RalphThis paper presents a new and very simple strategy for torque and flux control of ac machines. The method is based on model predictive control and uses one cost function for the torque and a separate cost function for the flux. This strategy introduces a drastic simplification, achieving a very fast dynamic behavior in the controlled machines. Experimental results obtained with an induction machine confirm the drive's very good performance. © 2012 IEEE.Ítem A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control(Institute of Electrical and Electronics Engineers Inc., 2018) Norambuena, Margarita; Rodriguez, Jose; Zhang, Zhenbin; Wang, Fengxiang; Garcia, Cristian; Kennel, RalphThis paper presents a new and very simple strategy for torque and flux control of ac machines. The method is based on model predictive control and uses one cost function for the torque and a separate cost function for the flux. This strategy introduces a drastic simplification, achieving a very fast dynamic behavior in the controlled machines. Experimental results obtained with an induction machine confirm the drive's very good performance. © 2012 IEEE.Ítem Latest Advances of Model Predictive Control in Electrical Drives - Part I: Basic Concepts and Advanced Strategies(Institute of Electrical and Electronics Engineers Inc., 2022-04-01) Rodriguez, Jose; Garcia, Cristian; Mora, Andres; Flores-Bahamonde, Freddy; Acuna, Pablo; Novak, Mateja; Zhang, Yongchang; Tarisciotti, Luca; Davari, S. Alireza; Zhang, Zhenbin; Wang, Fengxiang; Norambuena, Margarita; Dragicevic, Tomislav; Blaabjerg, Frede; Geyer, Tobias; Kennel, Ralph; Khaburi, Davood Arab; Abdelrahem, Mohamed; Zhang, Zhen; Mijatovic, Nenad; Aguilera, Ricardo P.The application of model predictive control in electrical drives has been studied extensively in the past decade. This article presents what the authors consider the most relevant contributions published in the last years, mainly focusing on three relevant issues: weighting factor calculation when multiple objectives are utilized in the cost function, current/torque harmonic distortion optimization when the power converter switching frequency is reduced, and robustness improvement under parameters uncertainties. Therefore, this article aims to enable readers to have a more precise overview while facilitating their future research work in this exciting area.Ítem Latest Advances of Model Predictive Control in Electrical Drives - Part II: Applications and Benchmarking With Classical Control Methods(Institute of Electrical and Electronics Engineers Inc., 2022-05-01) Rodriguez, Jose; Garcia, Cristian; Mora, Andres; Davari, S. Alireza; Rodas, Jorge; Valencia, Diego Fernando; Elmorshedy, Mahmoud; Wang, Fengxiang; Zuo, Kunkun; Tarisciotti, Luca; Flores-Bahamonde, Freddy; Xu, Wei; Zhang, Zhenbin; Zhang, Yongchang; Norambuena, Margarita; Emadi, Ali; Geyer, Tobias; Kennel, Ralph; Dragicevic, Tomislav; Khaburi, Davood Arab; Zhang, Zhen; Abdelrahem, Mohamed; Mijatovic, NenadThis article presents the application of model predictive control (MPC) in high-performance drives. A wide variety of machines have been considered: Induction machines, synchronous machines, linear motors, switched reluctance motors, and multiphase machines. The control of these machines has been done by introducing minor and easy-to-understand modifications to the basic predictive control concept, showing the high flexibility and simplicity of the strategy. The second part of the article is dedicated to the performance comparison of MPC with classical control techniques such as field-oriented control and direct torque control. The comparison considers the dynamic behavior of the drive and steady-state performance metrics, such as inverter losses, current distortion in the motor, and acoustic noise. The main conclusion is that MPC is very competitive concerning classic control methods by reducing the inverter losses and the current distortion with comparable acoustic noise.Ítem Model Predictive Control for Power Converters and Drives: Advances and Trends(Institute of Electrical and Electronics Engineers Inc., 2017-02) Vazquez, Sergio; Rodriguez, Jose; Rivera, Marco; Franquelo, Leopoldo G.; Norambuena, MargaritaModel predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the latest developments in MPC for power converters and drives, describing the current state of this control strategy and analyzing the new trends and challenges it presents when applied to power electronic systems. The paper revisits the operating principle of MPC and identifies three key elements in the MPC strategies, namely the prediction model, the cost function, and the optimization algorithm. This paper summarizes the most recent research concerning these elements, providing details about the different solutions proposed by the academic and industrial communities. © 2016 IEEE.Ítem Model Predictive Control for Power Converters and Drives: Advances and Trends(Institute of Electrical and Electronics Engineers Inc., 2017-02) Vazquez, Sergio; Rivera, Marco; Franquelo, Leopoldo G.; Norambuena, MargaritaModel predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the latest developments in MPC for power converters and drives, describing the current state of this control strategy and analyzing the new trends and challenges it presents when applied to power electronic systems. The paper revisits the operating principle of MPC and identifies three key elements in the MPC strategies, namely the prediction model, the cost function, and the optimization algorithm. This paper summarizes the most recent research concerning these elements, providing details about the different solutions proposed by the academic and industrial communities. © 2016 IEEE.Ítem Predictive Voltage Control of Direct Matrix Converters with Improved Output Voltage for Renewable Distributed Generation(Institute of Electrical and Electronics Engineers Inc., 2019-03) Zhang, Jianwei; Li, Lia; Dorrell, David G.; Norambuena, Margarita; Rodriguez, JoseThis paper proposes a predictive voltage control strategy for a direct matrix converter used in a renewable energy distributed generation (DG) system. A direct matrix converter with LC filters is controlled in order to work as a stable voltage supply for loads. This is especially relevant for the stand-alone operation of a renewable DG where a stable sinusoidal voltage, with desired amplitude and frequency under various load conditions, is the main control objective. The model predictive control is employed to regulate the matrix converter so that it produces stable sinusoidal voltages for different loads. With predictive control, many other control objectives, e.g., input power factor, common-mode voltage, and switching frequency, can be achieved depending on the application. To reduce the number of required measurements and sensors, this paper utilizes observers and makes the use of the switch matrices. In addition, the voltage transfer ratio can be improved with the proposed strategy. The controller is tested under various conditions including intermittent disturbance, nonlinear loads, and unbalanced loads. The proposed controller is effective, simple, and easy to implement. The simulation and experimental results verify the effectiveness of the proposed scheme and control strategy. This proposed scheme can be potentially used in microgrid applications. © 2013 IEEE.Ítem Sequential model predictive control of three-phase direct matrix converter(2019-01) Zhang, Jianwei; Norambuena, Margarita; Li, Li; Dorrell, David; Rodriguez, JoseThe matrix converter (MC) is a promising converter that performs the direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful tool for power electronic converters, including the MC. However, weighting factor design and heavy computational burden impose significant challenges for this control strategy. This paper investigates the generalized sequential MPC (SMPC) for a three-phase direct MC. In this control strategy, each control objective has an individual cost function and these cost functions are evaluated sequentially based on priority. The complex weighting factor design process is not required. Compared with the standard MPC, the computation burden is reduced because only the pre-selected switch states are evaluated in the second and subsequent sequential cost functions. In addition, the prediction model computation for the following cost functions is also reduced. Specifying the priority for control objectives can be achieved. A comparative study with traditional MPC is carried out both in simulation and an experiment. Comparable control performance to the traditional MPC is achieved. This controller is suitable for the MC because of the reduced computational burden. Simulation and experimental results verify the effectiveness of the proposed strategy. © 2019 by the authors.